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microTSS: accurate microRNA transcription start site identification reveals a significant number of divergent pri-miRNAs

Author

Listed:
  • Georgios Georgakilas

    (University of Thessaly)

  • Ioannis S. Vlachos

    (University of Thessaly
    Laboratory for Experimental Surgery and Surgical Research ‘N.S. Christeas’, Medical School of Athens, University of Athens)

  • Maria D. Paraskevopoulou

    (University of Thessaly)

  • Peter Yang

    (Regeneron Pharmaceuticals Inc.)

  • Yuhong Zhang

    (Regeneron Pharmaceuticals Inc.)

  • Aris N. Economides

    (Regeneron Pharmaceuticals Inc.)

  • Artemis G. Hatzigeorgiou

    (University of Thessaly)

Abstract

A large fraction of microRNAs (miRNAs) are derived from intergenic non-coding loci and the identification of their promoters remains ‘elusive’. Here, we present microTSS, a machine-learning algorithm that provides highly accurate, single-nucleotide resolution predictions for intergenic miRNA transcription start sites (TSSs). MicroTSS integrates high-resolution RNA-sequencing data with active transcription marks derived from chromatin immunoprecipitation and DNase-sequencing to enable the characterization of tissue-specific promoters. MicroTSS is validated with a specifically designed Drosha-null/conditional-null mouse model, generated using the conditional by inversion (COIN) methodology. Analyses of global run-on sequencing data revealed numerous pri-miRNAs in human and mouse either originating from divergent transcription at promoters of active genes or partially overlapping with annotated long non-coding RNAs. MicroTSS is readily applicable to any cell or tissue samples and constitutes the missing part towards integrating the regulation of miRNA transcription into the modelling of tissue-specific regulatory networks.

Suggested Citation

  • Georgios Georgakilas & Ioannis S. Vlachos & Maria D. Paraskevopoulou & Peter Yang & Yuhong Zhang & Aris N. Economides & Artemis G. Hatzigeorgiou, 2014. "microTSS: accurate microRNA transcription start site identification reveals a significant number of divergent pri-miRNAs," Nature Communications, Nature, vol. 5(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6700
    DOI: 10.1038/ncomms6700
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